Contextualized experiences require more than sensor data

These days, there is a lot of buzz around IoT (the Internet-of-Things), with predictions of an astronomic amount of connected devices in the near future, and market opportunities that are multiples of that. Based on affordable sensor technology embedded in all types of objects, IoT will connect our everyday life to the Internet and has the potential to drastically transform the way we live and work.

However, many of the current IoT solutions are still surprisingly disappointing from a use case perspective. Often, these solutions are limited to visualizing time series of sensor data or allow to remotely control devices via a smartphone. Moreover, most applications still require substantial explicit end-user interaction, even for tedious, repetitive tasks.

At waylay, we believe that IoT can be better. Future IoT applications will more and more rely on an invisible layer that resides in the cloud. That layer will sense its environment, reason about it, and act upon it. It will be programmable and take away some of the end-user burden by automating repetitive tasks. It will also give users a more personalized experience. In order to take more intelligent and abstract decisions, this layer will sense the environment via a variety of inputs.

More powerful IoT applications can be created when sensor information is enriched by information available in machine-readable format on the Internet. That interaction between the Internet and IoT is well illustrated by the following YouTube movie in which the billboard advertisement for apparel is adapted to local weather conditions retrieved from the Internet. Rather than considering IoT as an island on its own, IoT needs to become an integral part of the Internet. Sensor data, wearables, big data, social media data and location data can all go into the mix to create a personalized user experience (i highly recommend this 25min YouTube movie by RackSpace’s Robert Scoble titled ‘The Age of Context’).

Many current use cases seem constrained and gadget-alike and are often characterized by linking a single input to a single output (action). A few examples:

Change the colour of my Philips hue lamp when it is my birthday.

If the window is open, turn off the thermostat.

Blink the lights in the living room when the washing machine has finished.

More compelling IoT applications can be built when technology allows to dynamically combine multiple information streams. This provides richer, contextualized information about the environment and allows for more abstract reasoning and automation. So rather than blinking the lights on your birthday, would you not be interested in automatically switching on some lights at 7.30pm when nobody is at home, to mislead burglars? Or proactively monitor industrial machines based on the combination of sensor data and historical information on broken parts gathered via big data analysis?

As a side effect of the lack of input information (and the incapability to model lack of information or incomplete data), current automation algorithms are often plagued by either false positives or false negatives. Some industry surveys estimate the number of false positive alarms of alarm systems as high at 95%-97%. Combining multiple information streams can provide more information about what is actually going on, be more precise , reduce the amount of false positives/negatives and hence provide a more robust and meaningful user-experience.

At waylay, we have the technology that allows to build these more compelling end-user applications. waylay’s Cognition-as-a-Service platform allows to reason, decide and automate by combining sensors data with social media data, location based information and any API information available on the Internet.